ontology-generator

Generate ontological knowledge graphs from topics or text as InfraNodus wikilinks.

107|28|Updated Oct 26, 2025
One-click install
npx skills add https://github.com/infranodus/skills --skill ontology-generator
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ontology-generator
Source: https://github.com/infranodus/skills/tree/main/skill-ontology-creator
Command: npx skills add https://github.com/infranodus/skills --skill ontology-generator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generate ontological knowledge graphs from topics or text to structure information for visualization and analysis.

Core Features & Use Cases

  • Generate topic-based ontologies to map domain concepts, classes, and relationships.
  • Extract entities and relationships from input text or documents to populate knowledge graphs.
  • Output is formatted using InfraNodus wikilinks syntax for immediate paste into InfraNodus visualization and gap analysis.

Quick Start

Use the ontology-generator to create a wikilinks-based knowledge graph from the provided topic or text and paste the result into InfraNodus for visualization.

Frequently Asked Questions about ontology-generator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a knowledge graph from a topic or text?

Ontology-generator creates a knowledge graph by extracting entities and relationships from your input topic or text, then outputs them as wikilinks-formatted relations ready for InfraNodus visualization without additional formatting.

What is an ontology and why would I need one for knowledge graphs?

An ontology structures domain concepts, classes, and relationships hierarchically. Ontology-generator builds these automatically from topics or documents, enabling systematic visualization and gap analysis of how ideas connect in your knowledge domain.

Can I use the output directly in InfraNodus?

Yes. Ontology-generator outputs wikilinks syntax specifically formatted for InfraNodus, so you can paste results directly into InfraNodus for immediate visualization and AI-assisted gap analysis without conversion steps.

How does entity extraction work with existing documents?

Ontology-generator processes input text to identify and extract entities and their relationships, then structures them as interconnected wikilinks suitable for network visualization in InfraNodus.

What's the difference between topic-based and text-based ontology generation?

Topic-based generation maps domain concepts from a subject area you specify; text-based generation extracts entities and relationships from documents you provide. Both produce wikilinks output for InfraNodus visualization.

Can ontology-generator help identify gaps in my knowledge structure?

Yes. The wikilinks output is formatted for InfraNodus's AI-assisted gap analysis, which identifies missing relationships and concepts in your knowledge graph after visualization.